import cv2
import gradio as gr

def detect_faces(image):
    # Convert the image to grayscale for better detection
    gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    
    # Load the pre-trained face detection model from OpenCV
    face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")
    
    # Detect faces in the image
    faces = face_cascade.detectMultiScale(gray_image, scaleFactor=1.1, minNeighbors=5)
    
    # Draw rectangles around the faces
    for (x, y, w, h) in faces:
        cv2.rectangle(image, (x, y), (x+w, y+h), (255, 0, 0), 2)
    
    # Return the modified image and the number of faces detected
    return image, len(faces)

iface = gr.Interface(fn=detect_faces,
                     inputs=gr.components.Image(source="webcam", type="pil"),
                     outputs=[gr.components.Image(type="pil"), gr.components.Label()],
                     title="Face Detection",
                     description="This app detects faces in real-time from your webcam.")
iface.launch()